Detecting anxiety in individuals with Parkinson disease
Bibliographic record
Abstract
OBJECTIVE: To examine diagnostic accuracy of anxiety detection tools compared with a gold standard in outpatient settings among adults with Parkinson disease (PD). METHODS: A systematic review was conducted. MEDLINE, EMABASE, PsycINFO, and Cochrane Database of Systematic Reviews were searched to April 7, 2017. Prevalence of anxiety and diagnostic accuracy measures including sensitivity, specificity, and likelihood ratios were gathered. Pooled prevalence of anxiety was calculated using Mantel-Haenszel-weighted DerSimonian and Laird models. RESULTS: A total of 6,300 citations were reviewed with 6 full-text articles included for synthesis. Tools included within this study were the Beck Anxiety Inventory, Geriatric Anxiety Inventory (GAI), Hamilton Anxiety Rating Scale, Hospital Anxiety and Depression Scale-Anxiety, Parkinson's Anxiety Scale (PAS), and Mini-Social Phobia Inventory. Anxiety diagnoses made included generalized anxiety disorder, social phobia, and any anxiety type. Pooled prevalence of anxiety was 30.1% (95% confidence interval 26.1%-34.0%). The GAI had the best-reported sensitivity of 0.86 and specificity of 0.88. The observer-rated PAS had a sensitivity of 0.71 and the highest specificity of 0.91. CONCLUSIONS: While there are 6 tools validated for anxiety screening in PD populations, most tools are only validated in single studies. The GAI is brief and easy to use, with a good balance of sensitivity and specificity. The PAS was specifically developed for PD, is brief, and has self-/observer-rated scales, but with lower sensitivity. Health care practitioners involved in PD care need to be aware of available validated tools and choose one that fits their practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".